Joint Synoptic and Cloud Variability over the Northeast Atlantic near the Azores
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In this article, self-organizing maps (SOMs) are employed to objectively classify the 500-hPa geopotential height patterns for 33 years of reanalysis fields (ERA-Interim) into pretrough, trough, posttrough, ridge, and zonal flow categories.Abstract:
Marine boundary layer clouds are modified by processes at different spatial and temporal scales. To isolate the processes governing aerosol–cloud–precipitation interactions, multiday synoptic variability of the environment must be accounted for. Information on the location of low clouds relative to the ridge–trough pattern gives insight into how cloud properties vary as a function of environmental subsidence and stability. The technique of self-organizing maps (SOMs) is employed to objectively classify the 500-hPa geopotential height patterns for 33 years of reanalysis fields (ERA-Interim) into pretrough, trough, posttrough, ridge, and zonal-flow categories. The SOM technique is applied to a region of prevalent marine low cloudiness over the eastern North Atlantic Ocean that is centered on the Azores island chain, the location of a long-term U.S. Department of Energy observation site. The Azores consistently lie in an area of substantial variability in synoptic configuration, thermodynamic environ...read more
Citations
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Journal ArticleDOI
Midlatitude Oceanic Cloud and Precipitation Properties as Sampled by the ARM Eastern North Atlantic Observatory
Scott E. Giangrande,Dié Wang,Mary Jane Bartholomew,Michael Jensen,David B. Mechem,Joseph Hardin,Robert Wood +6 more
TL;DR: In this paper, an edited version of this paper was published by AGU. Copyright 2019 American Geophysical Union (AGU) and the authors have published an extended version of their paper.
Midlatitude Oceanic Cloud Precipitation Properties as Sampled By the ARM Eastern North Atlantic Observatory
Scott E. Giangrande,M. P. Jensen,D. Wang,Mary Jane Bartholomew,J. C. Hardin,David B. Mechem,Robert W. Wood +6 more
TL;DR: In this article, the contribution of low clouds (e.g., cloud top < 4 km) to the overall precipitation over midlatitude oceans is poorly understood, in part because of the lack of coupled, high-quality measurements of precipitation and low cloud properties.
Journal ArticleDOI
Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA)
TL;DR: The Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) campaign as discussed by the authors was motivated by the need of comprehensive in situ measurements for improving the understanding of marine boundary layer CCN budget, cloud and drizzle microphysics, and the impact of aerosol on marine low cloud and precipitation.
Journal ArticleDOI
Vertical profiles of trace gas and aerosol properties over the eastern North Atlantic: variations with season and synoptic condition
Yang Wang,Yang Wang,Guangjie Zheng,Michael Jensen,Daniel A. Knopf,Alexander Laskin,Alyssa Matthews,David B. Mechem,Fan Mei,Ryan C. Moffet,Arthur J. Sedlacek,John E. Shilling,Stephen R. Springston,Amy P. Sullivan,Jason Tomlinson,Daniel P. Veghte,Rodney J. Weber,Robert Wood,Maria A. Zawadowicz,Jian Wang +19 more
TL;DR: In this article, the authors examined the key processes that drive the cloud condensation nuclei population in the MBL using comprehensive characterizations of aerosol and trace gas vertical profiles during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign.
References
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TL;DR: In this paper, the authors proposed a method called the "gap statistic" for estimating the number of clusters (groups) in a set of data, which uses the output of any clustering algorithm (e.g. K-means or hierarchical), comparing the change in within-cluster dispersion with that expected under an appropriate reference null distribution.
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Estimating the number of clusters in a dataset via the gap statistic
TL;DR: The gap statistic is proposed for estimating the number of clusters (groups) in a set of data by comparing the change in within‐cluster dispersion with that expected under an appropriate reference null distribution.
Journal ArticleDOI
Clustering of the self-organizing map
Juha Vesanto,Esa Alhoniemi +1 more
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